15.8% of Developer Comments About AI SEO Are Positive, Against 4.6% for Classic SEO

Summary

Ask a developer what they think of SEO and you will often get a groan. Years of recipe pages with the recipe at the bottom and articles padded to rank have left a mark. So we wanted to know whether the newer idea of optimizing for AI answers starts from the same low point.

We pulled every Hacker News comment since 2023 that mentions AI SEO, generative engine optimization (GEO), answer engine optimization (AEO), LLM optimization or AI visibility. Our team read a random sample alongside a matched sample of comments about classic SEO and coded each one.

AI SEO comes out ahead, though from a low base. Leaving out people promoting their own tools, 15.8% of AI SEO comments were positive against 4.6% for classic SEO. Most comments about both were still neutral or negative.

What we measured

We used the public Hacker News table on Google BigQuery. AI SEO comments are those mentioning generative or answer engine optimization, GEO or AEO alongside SEO, LLMO, AI SEO, LLM SEO, SEO for AI or AI visibility (371 comments from 2023 to September 2026). Classic SEO comments mention SEO or search engine optimization without any of those terms (12,643 in the same period, 4,686 of them in 2025 and 2026).

Our team read random samples of 125 AI SEO comments and 123 classic SEO comments, using 2025 and 2026 for classic SEO because 86.8% of AI SEO comments fall in those years. We removed off-topic matches (for example geographic uses of GEO or AI-written spam described as AI SEO), leaving 113 and 122. Each was coded positive, neutral or negative toward the practice, and flagged if the writer was promoting their own product or service. With these sample sizes, each share has a margin of error of up to about 9 to 11 percentage points; the gap in positive shares is statistically significant at 95% confidence.

AI SEO gets more praise and less scorn

We report two cuts. The first counts every relevant comment. The second leaves out comments where someone was pitching their own tool or service, which gives a cleaner read on what other people think.

Either way you cut it, AI SEO draws a higher share of positive comments and a lower share of negative ones. Positive comments about AI SEO tended to describe it as a real shift worth preparing for, or reported early results from making content clearer for AI tools.

Still, positive comments are a minority in both groups. Developers mostly discuss either practice in neutral or critical terms.

The worry has moved from spam to manipulation

The complaints differ. Classic SEO is blamed for what it already did to search results. AI SEO is blamed for what people fear it will do to AI answers.

For AI SEO, the most common fear was that companies will seed fake reviews, forum posts or comparison pages so assistants recommend them. The second was skepticism that the tools can measure or change anything. For classic SEO, almost every complaint came back to junk pages crowding out useful ones.

The conversation is growing fast, and so is the selling

AI SEO is a young topic on Hacker News, and a large share of the talk comes from people launching tools.

Comment volume jumped in 2025 and has kept climbing. A third of the sampled AI SEO comments were product pitches, which suggests how crowded the tool market has become and may be part of why some readers are skeptical.

What this means

Technical audiences are more open to AI SEO than to old-school SEO, but their main fear is manipulation. The approach that earns trust is the boring one: accurate facts about your business, consistent across your site and the places AI tools read, with no fake reviews or seeded posts. That is also what holds up when assistants get better at spotting games. Any AI search optimization services you pay for should be built the same way.

If you hire help, ask how they measure results and what they will not do. Our free AI visibility audit shows where you stand today using real prompts, and our answer engine optimization services stick to fixes that hold up.

Limits

Sentiment was coded by our team on random samples of 125 and 123 comments. Different coders could label some comments differently, and each share carries a margin of error of up to about 9 to 11 points.

AI SEO terms are new and inconsistent, so keyword matching misses some comments and catches some off-topic ones, which we removed by hand.

The classic SEO sample is drawn from 2025 and 2026 to match the timing of AI SEO talk; earlier years could differ.

Hacker News commenters are mostly developers and founders, who are often more critical of marketing than business owners are.

Dead and deleted comments carry no text in the dataset and are excluded.

Frequently asked questions

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